Abstract
Reducing the environmental impact of food production represents one of the most significant challenges to increase sustainability. The ECOWHEATALY project - Evaluation of policies for enhancing sustainable wheat production in Italy - aims at tackling the issue of environmental impacts of the wheat production system in a dynamic socio-economic and environmental interaction setting by analyzing the changes in farmers' behavior after the adoption of green policies by the national authorities and in combination with the level of price in the main worldwide markets.   In the context of the ECOWHEATALY project, the behavior of farmers operating in Italy is classified into a few macro-typologies according to the farm environmental impact in terms of pesticides, fertilizers, and fossil fuel uses, with their costs and revenue profiled in alignment. To this end, ECOWHEATALY will take advantage of the Farm Accountancy Data Network (FADN), an extensive database of national surveys providing harmonized micro-economic data, including resource uses and costs, for farms in the European Union (EU). Specifically, data on farms' uses of pesticides, fertilizers, and usage time of agricultural machinery (as a proxy of fossil fuel consumption) are fed into the Agglomerative Hierarchical Clustering (HC) algorithm, an unsupervised state-of-the-art machine learning technique widely employed for clustering purposes. The cluster analysis, configured with the cluster number set to 5 based on the corresponding HC dendrogram, yields five distinctive groups, each briefly characterized as follows: G1) Farms exhibiting a pronounced inclination for excessive pesticide use. This group also records the highest quantity of nitrogen per hectare. Notably, these farms utilize few hours of agricultural machinery, suggesting concentrated applications of chemicals; G2) Farms applying a significant amount of nitrogen per hectare but minimal or no phosphorus and potassium, indicating unbalanced fertilizer use tilted towards nitrogen; G3) Farms displaying a high usage of agricultural machinery, accompanied by substantial doses of phosphorus-based fertilizer, moderate quantities of nitrogen, and minimal pesticide use; G4) Farms with a relatively medium to low environmental impact, identified by fertilizer use dominated by phosphorus and followed by potassium; G5) Farms with a relatively low environmental impact, distinguished by lower and balanced use of fertilizers and pesticides. The resultant groups are characterized using FADN micro-economic variables, including current costs, net farm income, subsidies, and salable gross production. This profiling will enable the ECOWHEATALY project to undertake additional activities to identify green incentives capable of steering farm practices toward greater sustainability. The transformation of the Italian wheat production system, resulting from firms transitioning between different types due to agricultural and environmental policies, will be assessed through the development of an agent-based model at the national level. Moreover, ECOWHEATALY will proceed to gauge the environmental impact of policies by implementing the Life Cycle Assessment (LCA) methodology using the model's outputs, introducing a novelty in the field of green policy evaluations.  
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